724_Final Report.pdf - North Pacific Research Board

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Lab analysis Lipids were extracted from eider adipose tissue samples and homogenates of whole individual mussel (without shell, N = 15) and silverside (N = 39) using a modified Folch technique (Folch et al. 1957, Iverson et al. 2001). Individual krill and Mazuri pellets were pooled into samples so that the combined sample weight was approximately 1.5 g. Between two and six individual krill were pooled per sample (N = 39) and between 14 and 17 individual Mazuri pellets were pooled per sample (N = 23). Clams were already shelled and pre-cut into 2.0 – 4.0 g pieces and shipped to ASLC in frozen blocks. Each pre-cut piece was analyzed as an individual sample (N = 15). FA methyl esters (FAME) were prepared using an acidic transesterification (Budge et al. 2006). The presence of fatty alcohols resulting from the transesterification of wax esters in diet items was determined using thin layer chromatography. In order to account for wax esters in diets, the alcohols of which are deposited as their corresponding FA in the adipose tissue (Budge and Iverson 2003), wax ester alcohols were converted to their respective FAs according to Budge et al. (2006). FA methyl esters were quantified using temperature-programmed gas liquid chromatography on a Perkin Elmer Autosystem II Capillary FID gas chromatograph fitted with a 30m x 0.25 mm id column coated with 50% cyanopropyl-methylpolysiloxane (DB-23) and linked to a computerized integration system (Varian Galaxie software) according to Iverson et al. (2002). Each chromatogram was manually assessed for correct peak identification and reintegrated, where necessary. Qualitative analysis of diet items and eider FA Multivariate analyses were conducted using discriminant function analysis (DFA) followed by classification using a jack-knifing procedure (leave-one-out cross-validation) to assess how well FAs separate 1) diet items, 2) eider biopsies by species, diet and biopsy date, and 3) diet items and eider biopsies. Given restrictions on variables used in DFA (n-1of smallest sample size), we selected 14 diet item FAs which had the highest variance and overall means of the 72 total FAs identified (14:0, 16:0, 13
16:1n-7, 18:0, 18:1n-9, 18:1n-7, 18:2n-6, 18:3n-3, 18:4n-3, 20:1n-9, 20:1n-7, 20:5n-3, 22:5n-3, 22:6n-3), and 7 eider adipose tissue FAs with the highest observed variance across eider groupings (14:0, 16:0, 16:1n-7, 18:0, 18:1n-9, 18:2n-6, 22:6n-3), and 7 FAs with the highest observed variance and means across all diet items and eider samples (14:0, 16:0, 16:1n-7, 18:1n-9, 18:2n-6, 20:5n-3, 22:6n-3). The subsets of FAs used in these analyses are also known to be derived dominantly or solely from dietary intake (Iverson et al. 2004). Proportional representation of each FA was recalculated for this subset and arcsine square-root transformed prior to analysis. We used quadratic DFA because the within-group covariance matrices in our dataset were not homogenous (Bartlett’s test, P < 0.001), which may result in poorer separation between groups, although there is little evidence that moderate violation significantly alters cross-validated classification success (McGarigal et al. 2000). CC and FA subset selection An integral part of the QFASA model is the use of CCs to account for predator lipid metabolism by weighting individual FAs according to their tissue deposition relative to diet (Iverson et al. 2004, 2006, 2007). We calculated eider CCs by dividing levels of individual FA in eiders from biopsy 1 (Day 0) by levels of those same FA in Diet 1, which was fed to the eider for 69 days before this first biopsy (sensu Iverson et al. 2004). Not all FAs provide equal information about diet due to consumer metabolism, origin (predominantly dietary versus biosynthesis), and levels found in tissue (trace levels may not be correctly identified) (Iverson et al. 2004). Therefore, it is important to select an appropriate FA subset when using QFASA to estimate diet. Twenty-five new FA subsets were developed based on two published subsets that include FAs that could arise from dietary origin alone (Dietary, 33 FAs) or include the Dietary subset along with 8 FAs whose levels in a consumer are also influenced by diet (Extended Dietary, 41 FAs) (Iverson et al. 2004). FAs were omitted from the published subsets in order of highest variability 14
Page 1 and 2: NORTH PACIFIC RESEARCH BOARD PROJEC
Page 3 and 4: TABLE OF CONTENTS STUDY CHRONOLOGY
Page 5 and 6: snails (Petersen et al. 1998, Lovvo
Page 7 and 8: een employed in eiders to evaluate
Page 9 and 10: CHAPTER 1. Validating quantitative
Page 11 and 12: Abstract Fatty acid (FA) signature
Page 13 and 14: migration, or how the diets of juve
Page 15: were switched to Diet 3 which consi
Page 19 and 20: The diets of captive eiders were es
Page 21 and 22: Calibration coefficients (CCs) and
Page 23 and 24: Discussion The results from this ca
Page 25 and 26: appropriate for estimating a consum
Page 27 and 28: Ideally, captive studies should mim
Page 29 and 30: Acknowledgments Financial support w
Page 31 and 32: Federal Register. 1997. Endangered
Page 33 and 34: Raclot, T., Groscolas, R., and Cher
Page 35 and 36: Table 2. Sum of the squared errors
Page 37 and 38: Figure 5. QFASA estimates using the
Page 39 and 40: Figure 2. 2nd discriminant function
Page 41 and 42: Figure 4. proportion proportion 1.0
Page 43 and 44: Appendix 1. Fatty acid (FA) subsets
Page 45 and 46: CONCLUSIONS The results from this c
Page 47 and 48: we incorporated into our calculatio
Page 49 and 50: There is still much work to be done
Page 51 and 52: ACKNOWLEDGEMENTS Funding was provid
Page 53 and 54: Harrison, N.M. 1984. Predation on j
Page 55: APPENDIX A: ASLC Fact Sheet 52

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